1

Personal Gaming Team Tech Transform

Brice Nzeukou

Kunmi Jeje

Stephen Schwee

David Carrega

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Table of Contents

Executive Summary ………………………………………………………………………………………………………………………………. 3

Objective ………………………………………………………………………………………………………………………………………… 3

Approach ………………………………………………………………………………………………………………………………………… 3

Conclusion ………………………………………………………………………………………………………………………………………. 3

Introduction ………………………………………………………………………………………………………………………………………….. 5

History of Videogames ……………………………………………………………………………………………………………………. 5

History of AI ……………………………………………………………………………………………………………………………………. 6

Intersection of AI and Videogames …………………………………………………………………………………………………. 7

Description of Technology …………………………………………………………………………………………………………………….. 8

Data Mining ……………………………………………………………………………………………………………………………………. 8

Personal Gaming …………………………………………………………………………………………………………………………….. 8

Roadblocks to Adoption ………………………………………………………………………………………………………………………… 9

Power of Executives ………………………………………………………………………………………………………………………… 9

Data Mining Considerations ……………………………………………………………………………………………………………. 9

Privacy ……………………………………………………………………………………………………………………………………………. 9

Projections ………………………………………………………………………………………………………………………………………….. 10

Industry is Ripe for Disruption …………………………………………….………………………………………………………… 10

Hypotheses ………………………………………………………………………………………………………………………………….. 10

Rationale ………………………………………………………………………………………………………………………………………. 11

Scenario ………………………………………………………………………………………………………………………………………………. 15

Conclusions …………………………………………………………………………………………………………………………………………. 16

Interviews …………………………………………………………………………………………………………………………………………… 17

References ………………………………………………………………………………………………………………………………………….. 18

Appendix A : S-Curve ………………………………………………………………………………………………………………………….. 20

Appendix B : Team Dynamics ………………………………………………………………………………………………………………. 21

3

Executive Summary

Objective

For the past few years, innovation within the video game industry has plateaued. Six years ago

the current batch of consoles hit the market with grand visions of the next generation of

gaming. Unfortunately, very few games could live up to the hype surrounding these visions. The

objective of this paper is to analyze innovation opportunities within the video game industry.

The focus of our analysis will be upon the application of artificial intelligence (AI) to gaming and

real life.

Approach

We employed the following techniques to analyze the video game industry

1. Interviews with Academic Researchers 2. Interviews with Game Designers 3. Interviews with AI Programmers 4. Secondary Research from Gaming and Venture Investing Websites

Conclusions

Advanced AI could be implemented to radically transform video game experiences for the

better, but it will not be implemented in the near future. Game design is both a science and an

art. The science, the advanced AI, is ready for implementation, but the art, the actual game

design, is questionable. Until a total genius successfully creates and tests a grand artistic vision

that incorporates advanced AI as a key gameplay element, no videogame publisher will

dramatically change the types of games that they offer. It is too risky.

Despite the lack of innovative games, AI will be instrumental in innovative developer tools and

in the transformation of entertainment consumption. The developer tools of the future will

increase productivity through the automation of tedious tasks, such as creating a forest of

unique trees. This innovation is an incremental improvement that will not disrupt the

videogame industry. The transformation of entertainment consumption, hereafter referred to

as personal gaming, will be the focus of our paper because it is a disruptive technology.

4

Introduction

History of Videogames

Videogames technically began in 1947 when Thomas T Goldsmith and Estle Ray Man filed a

patent for a machine in which a cathode ray tube could be manipulated to simulate firing at

“air-borne” targets [1]. Similar games followed, including OXO a graphical version of tic-tac toe

created by A.S. Douglas in 1952 at the University of Cambridge [2]. These early games and their

derivatives were developed as hobby projects on university mainframe computers.

The 1960s brought about much innovation in the basic science behind videogames. From 1959

– 1961, a collection of interactive videogames were developed at MIT. Four games were of

particular importance. Mouse in the Maze was a mouse maze simulator. HAX was a primitive

music maker. Tic-Tac-Toe was adapted to a touch screen. Spacewar! was a simple two player

shooting game that was widely distributed via the internet [3]. In 1966, Ralph Baer and Bill

Harrison, two engineers at Sanders Associates, a military electronics contractor, created the

first home console prototype [4].

The 1970s brought about the first major commercialization of videogames. Atari created the

first profitable arcade game, Pong, in 1972 [5]. Magnavox created the first profitable home

video game console with the Odyssey [6]. RCA and a variety of other manufacturers entered the

console business. Most of the games for home consoles were Pong clones and the industry took

a dive in 1977 when some manufacturers began to sell at a loss to clear stock [7]. During this

time, university mainframe game development blossomed. Mainframe computer games were

often made illicitly by making questionable use of university resources. These games were not

sold for profit. It must be noted that during this time, videogame production was still a niche

skill. More often than not, videogames were developed entirely by one person [8].

The 1980s brought about large changes in the videogame landscape. Arcades boomed, but the

old manufacturers of consoles from the seventies went into financial ruin in 1983. Some

5

attribute the crash to poor games, such as ET [9]. Nevertheless, the videogame industry was

saved by Nintendo in 1985 with the NES. With the NES, a renaissance of gaming came about.

New genres and new experiences were created [10].

From the 1990s onward, small incremental changes have characterized the videogame industry.

3D Graphics became the standard. The Arcade business slowly died in the 90s as home consoles

ate away at their customers. Because of Moore’s Law, home consoles became more powerful

than arcade machines in 1998 with the launch of the Dreamcast [11 Add Reference]. Dreamcast

also marked the beginnings of significant online multiplayer. The development of the 2000s and

later will be discussed in detail later.

The constant throughout gaming history, until the 2000s, has been the information asymmetry

between publishers and gamers. Before 1981, there were no consumer-oriented video gaming

magazines [11]. Even after these publications came into being, most people did not consult

these magazines. So consumers were left with renting games before purchasing them, playing

games that other friends own, or taking a risk with each purchase. On the publisher’s side, not

much was known about consumers and their preferences aside from the quarterly sales figures.

Today, this information asymmetry has become smaller on the consumer side with the advent

of online gaming forums. We believe that publishers will be able to decrease the information

asymmetry on their side of the market by using AI.

History of AI

Artificial intelligence is the intelligence of machines and the branch of computer science that

aims to create it. AI textbooks define the field as “the study and design of intelligent agents”

[12] where an intelligent agent is a system that perceives its environment and takes actions

that maximizes its chances of success. John McCarthy, who coined the term in a conference at

Dartmouth in 1956, defined it as “the science and engineering of making intelligent machines”

[13]. After the conference, AI research made tremendous progress with aid from the US

government [14]. However, the optimism of the early researchers ended in the 1970s when

6

funding was cut due to insurmountable technological hurdles, such as limited computing

power, that rendered most of their findings inapplicable to the real world [15]. Heavy AI

research resumed in the 1980s when the Japanese government, British government, and

American corporations resumed funding ambitious AI projects. By the end of the 1980s, funding

was cut yet again. After this AI bubble, AI research became extremely fragmented into

subdomains such as machine learning, data mining, and object tracking.

Intersection of AI and Video Games

Adam Noonchester of Insomniac Games offered insight into the intersection of AI and

videogames. Academic researchers are interested in creating intelligent machines. AI in

videogames is concerned with creating a fun experience. The creation of realistic and intelligent

enemies, something only hardcore gamers desire, is a design choice that might alienate a lot of

potential customers. This point is discussed in detail in our roadblocks to adoption section.

Because of the potential economic backlash from a niche game, AI could be better used outside

of gameplay to enhance the end user experience. One such example of this would be a behind

the scenes algorithm that quantifies the amount of fun that a player is experiencing at any

given time. We believe that this “fun algorithm” can be implemented and enhanced through

the application of data mining and personal gaming.

7

Technology Description

Data Mining

Data mining is the process that results in the discovery of new patterns in large data sets via the

use of AI technology [16]. The goal of data mining is to extract knowledge from an existing data

set and convert this information into an understandable structure that can then be used. The

process of data mining can be divided into six main processes. The first process called anomaly

detection attempts to detect outliers in the information or data errors that may require further

investigation. The second process is association rule learning, which searches for relationships

between variables. The third process is the clustering of similar data into groups. The fourth

process is classification, which is used to classify new data and place them into groups. The

fifth process is regression, which attempts to find a function to model the data. Finally the last

process is summarization, which attempts to provide a compact representation of the

respective data set. [17]

Personal Gaming

An example of how AI can be used in data mining for enhanced video game experience is in

personal gaming, a new paradigm of videogame interaction being developed by Will Wright.

Hivemind, his latest working title, embodies personal gaming. HIvemind will be a cross-

platform experience that allows players to connect through mobile devices, computers, and

consoles, focusing on gamifying the player’s life. Personal gaming requires a lot of information

to be shared by the player; however, the information is used exclusively to build a personal

gaming experience for the player. Thus, game experience can change based on the player’s

emotional state and patterns that develop in the player’s life. This creates the “personal

gaming” experience that immerses the player into the real world through connectivity with

sites like Facebook and Meetup. Data mining will play a key role in the implementation of

“personal gaming” because an enormous amount of data needs to be mined and interpreted

using AI [18].

8

Roadblocks to Adoption

Power of Executives

A major issue with the development of AI in video games lies in the power of the executives.

The executives of gaming companies have the last say on the games that are produced. Our

contact at Insomniac games, Joel Goodsell, explained that the choice of not using AI in a video

game is a design choice. Games such as Call of Duty and Halo, basic first person shooters that

use primitive AI for enemies in the game, are characteristic of most of the popular games for

the past decade. Gamers have expectations for certain franchises to behave in certain ways.

Because these current video games are selling quite well, executives are reluctant to deviate

from their formulas for success. This is why we will not see a high level of AI in game play for

the next generation of game video games.

Data Mining Considerations

Two different tech challenges lie in this issue of data mining. The first challenge that there are

many different formats of information that the AI has to aggregate [19]. Creating a universal

format for all of this data, with the capability of expanding to new data types, will be a

challenge. An even more pressing issue is the quantification and connection of data. How do

you quantify fun? How do you quantify relevant user behavior? How do you make relevant

suggestions based upon this data? It is beyond the scope of this paper to investigate these

questions in detail, but AI can theoretically answer all of these questions [19]. Cloud computing

will probably be used in the actual analysis of the data. Personal gaming companies could run

their own server farms, or they could just use the spare CPU cycles of all platforms that run

their software.

Privacy

The second issue that arises with personal gaming is privacy and security of information [20].

All of the information that is being mined and analyzed by the AI, most likely by cloud

computing, needs to be protected and kept private[21]. Beyond the actual security of personal

information is the perception of security from end users. End users must not feel violated

9

because some software knows more about them than their friends do. We believe that a

successfully marketing campaign would calm most user fears.

10

Projections

Industry is Ripe for Disruption

Currently, the gaming industry is undergoing dramatic changes. Retail sales are dwindling. April

2012 marked $1 Billion in retail videogame sales. However, that figure is 32% less than the

retail sales of 2011[22]. Moreover, April marked the fifth month of declining retail sales. Big

publishers have hurt the most from these turn of events. One such example is THQ, one of the

dominant players in the video game industry during the 90s, who has had to sell licensing rights

and dismantle some of its studios for financial reasons [23]. Because of these massive layoffs,

plenty of talented programmers and designers are developing their own indie games or are

joining other publishers that are investing in new mobile gaming studios [24].

Given the financial climate of the gaming industry, innovative gameplay utilizing advanced AI

will not be a major disruptive technology because publishers are unwilling to take huge risks

right now. It would only take one major flop to put any publisher into crisis mode. Publishers

are more likely than ever to release formulaic games with smaller budgets to mitigate their risk.

Nevertheless, advanced AI algorithms within the realm of data mining might prove to be

disruptive within the realm of videogames. Essentially publishers need to know the answers to

these two questions: (1) How does one price a video game? (2) Which customers does one

make a game for?

Hypotheses

1. Mobile Gaming will become a Significant Part of Every Publisher’s Portfolio 2. Free to Play Will Become the Standard Pricing Model of Mobile Gaming 3. Several Powerful Recommendation and Digital Distribution Channels Will Emerge 4. A Developer Independent Recommendation Engine and Distribution Channel Will

Emerge and Dominate 5. The Developer Independent Recommendation Engine will Extend to Real Life

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Rationale

Mobile Gaming Will Become a Significant Part of Every Publisher’s Portfolio (2 years)

By the year 2016, one billion consumers will have smartphones. In the US alone, consumers will

own 257 million smartphones and 126 million tablets [25]. Currently, 70% of smartphone users

have over 10 apps [26]. Of these apps, games are the most popular. On average, smartphone

users spend 7.8 hours a month playing games [27]. These numbers cannot be ignored. To be

competitive large videogame publishers must enter the mobile gaming market and find a way

to monetize players to the fullest extent.

Among the larger publishers, EA and Ubisoft are making the first moves. EA is set to publish

Outernauts, an Insomniac Game, later this summer. They are targeting 13 – 25 year old

demographic that desires the depth of Pokémon within a Facebook game [28]. Outernauts is an

entirely new franchise. Ubisoft is taking another approach. Instead of creating a new franchise,

Ubisoft is expanding its old Ghost Recon franchise. Essentially the mobile app, Facebook game,

console game, and PC game will all be connected. Playtime in any of the platforms will advance

the overall game and unlock new weapons and levels for the single player experience [29]. This

strategy rests upon the fact that most people, including hard core gamers, are on Facebook.

These gamers cannot always be at their consoles, but they can always log in a few minutes of

gameplay on their mobile phone.

Free to Play Will Become the Standard Pricing Model of Mobile Gaming (2 years)

There has been a shift in the revenue potential of the business models employed by the gaming

industry. With the emergence of social/casual mobile and online gaming as an ever growing

sector of the gaming market, the free to play or “freemium” games with micro transactions and

subscriptions model will be the focus of many game developers. This business model does not

charge a price for the game, but allows users to upgrade to a better version of the game with

more features for a premium. Game developers also can put a focus on micro transactions in

the game play, such as buying improved weapons or increased ammo storage. This will be the

dominate strategy for game developers because gamers are constantly playing on the go, 33%

12

of gamers play games on their smartphones [30]. The growth of the sector has been staggering

with online and mobile gaming increasing from 32% of global revenue in 2009 to a projected

50% in 2014 [30]. Chinese company Tencent has already capitalized on the value of the

casual/social online and mobile gaming sector. Tencent holds a dominant stake in the Chinese

online/mobile market. Even in the volatile gaming market, Tencent was able to sustain 49%

growth for five financial quarters starting in the third quarter of 2009 [30].

Piracy has also been an issue for console games. Moving towards online and mobile gaming

decreases the chance for piracy while increasing distribution. Chinese gaming company Tencent

has solved the piracy problem in China. Its free to play model does away with the need for

piracy because gamers do not have to pay to play, the original reason for pirating games.

Another plus of the free to play market is that it reduces direct price competition. Therefore

companies can focus on attracting customers through content. There will be some competition

on the pricing of in game content, but those indirectly affect the ability of gamers to play

competitors’ games.

We have already seen many games that employ the free to play model. A relatively new studio,

U4iA has plans to release a free to play first person shooter in beta testing this summer. It

boasts user customization and ‘the most competitive multiplayer action ever seen within a

browser’ [31]. Other notable games that employ the free to play strategy are Lord of the Rings

Online, and League of Legends. These games have a dedicated gamer base and revenue

streams due to upgrades and in game and downloadable content. Additionally, the free to play

model was endorsed by the speakers at the Caltech-MIT Forum on Mobile Gaming.

Several Powerful Recommendation and Digital Distribution Channels will Emerge (3 years)

With the increased ease of publishing video games, as well as the explosion of digital and online

video games, gamers are going to be overwhelmed by the number of options. Reviews tend to

be misleading and biased, therefore a need for a standard rating and recommendation engine

would be a disruptive concept to the gaming industry. Distribution has also been a challenge for

13

many gaming companies. Now that digital releases of video games are becoming more

common, it is becoming more necessary to have a centralized distribution channel. Valve

Software uses Steam, a computer program that distributes their games as well as other gaming

companies. EA has Origin, a similar program to Steam that centralizes downloads and game

extras for their games only. EA and Valve are ahead of the curve in establishing this centralized

application model. This distribution channel model is meant to service the hardcore gamer and

allow for direct access to companies such as EA and Valve. There are also game consolidation

engines that operate in the social/online gaming sector. Aeria Games is a company that

consolidates free to play MMO profiles for over 30 games, “Ignite was created by Aeria Games

to provide a comprehensive, easy-to-use distribution mechanism for free-to-play developers

while giving our players one-click access to their favorite games, community features, and

support”[32]. With plans to move into the mobile sector, companies like Aeria Games will be

the leaders in game distribution and information consolidation.

A Developer Independent Recommendation and Distribution Channel will Emerge and

Dominate (5 years)

Although we foresee a shift to centralized distribution channels, there will still be a need for a

developer independent channel that services the social and mobile gamers and developers.

This model is employed by both Apple mobile platform and the Google Android platform. Both

app stores are battling for market share in the app markets. Currently, 55% of the top 100

iPhone paid and free apps are games. This suggests that the “app store” is a viable way of

promoting and distributing certain types of games. Google is second in this market, with a total

apps growth rate that is five times that of Apple [30]. Therefore, a centralized database like

Apple’s iTunes, although not disruptive, would still be able to take over the market if they were

able to consolidate the information from both platforms in order to make recommendations

and distribute the right games to gamers.

The Recommendation Engine will Extend to Real Life with Personal Gaming (10 years)

Personal gaming will be an emerging frontier in the gaming industry. With increasing capability

14

of data collection and data processing, AI will be used to help identify trends in personal data.

This will allow many companies to target different people with different games and products.

There are companies already starting to enter the social data mining market. Kontangent is an

analytics tools company that is expanding its capabilities to the mobile platform, “Kontangent’s

gaming analytics tool updates its web-based dashboard with feedback on social game usage

every 10 seconds” [33]. Companies are now looking to go even beyond the scope of targeted

video games, to essentially ‘gamifying life’. This idea has been expressed by notable game

developer Will Wright, as he believes that personal gaming will have the ability to “customize

itself for the individual player, taking into account aspects of player’s real-life situation as

elements of the game” [34]. Essentially games will change to suit the unique needs and

routines of the user.

15

Scenario

At first glance, Bob seems like your typical 22 year old American male. He has a smartphone that is

connected to his Facebook and a variety of social games. When not on the go, he enjoys his downtime

on his computer and Xbox 360. However, Hivemind, a personal gaming application, has been working

behind the scenes and mining all of his digital data to create an accurate digital mapping of him and

connect him with other interesting people. Hivemind has not intruded his privacy. He actually installed

Hivemind on all of his devices. This choice of his will impact him for the better. Hivemind knows Bob

better than he knows himself.

Bob recently received a job offer from Volkswagen. Being a mechanical engineer looking for work, he

took the job without even visiting Chattanooga, TN. After his first week of work, he hates his job. He

doesn’t actually hate his job. He just hates the fact that all of his friends are in Sunny Southern California

and the only person he knows in Chattanooga is his third cousin that he has not seen in ten years. It

might come as a shock to you, but Hivemind knows all of this.

To improve Bob’s wellbeing, Hivemind suggests playing MLB 12 The Show, a baseball game. Bob takes

the suggestion and starts playing. He begins to play the game every night after work. Every time he

plays the game, he chooses the LA Dodgers as his team. Hivemind recognizes that the LA Dodgers are his

favorite team, so it recommends a meet up for Dodgers fans in Chattanooga, TN. Bob reluctantly goes

on the basis that he actually does have nothing better to do.

Bob drives to the Tremont Tavern with no expectations. He arrives and sees a bunch of guys decked out

in Dodger blue. He immediately feels a connection with these people. After a few beers over the game,

Bob actually feels like he has some friends. Hivemind knows this because his Facebook network grew

after the meetup. Later Hivemind suggests playing UFC Unleashed, a fighting game that the people at

the meetup have played together in the past. Bob buys the game and has plenty of fun. Hivemind

predicts that Bob would actually like to engage in more physical activity, so it alerts Bob of a deal at the

Chattanooga Jiu Jitsu Academy. Bob joins and realizes that his life has become a lot more interesting

since he installed Hivemind on all of his devices. It turns out that Chattanooga, TN is not that bad after

all.

16

Conclusion

The gaming industry, although stagnant in technology applications within video games, is

headed in a very interesting direction. Game companies are becoming entertainment

consolidators. They are consolidating the old console game model and expanding the

promising social and mobile gaming sector. Given that consoles supply more than a platform to

play video games, these gaming companies will become entertainment experts and eventually

they will be able to personalize each system with recommendations for the user.

The true innovation in the gaming industry isn’t going to come from console hardware, or in

game software, but in the way that games interact with people. Gamers are going to be looking

for the next gamer experience, a personalized one. Applications will tailor recommendations

for games, TV shows, movies, and entertainment content for the user. It will be the task for AI

to sift through enormous amounts of user data, and find relevant trends that can be translated

into potential revenue streams. Games will even adjust their in game content to match user

routines and identified trends. Personalized gaming is the new frontier for video games.

17

Interviews

Academic Researchers

Ken Stanley, Professor of Computer Science at UCF

Game Designers

Doug Church, Valve Software

Joel Goodsell, Insomniac Games

Stephane Bura, Independent

AI Programmers

Ian McMeans, Insomniac Games

Adam Noonchester, Insomniac Games

18

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29. http://venturebeat.com/2012/05/21/ghost-recon-commander-offers-headshots-in-a-facebook-game-hands-on-preview/

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20

Appendix A: S – Curve

21

Appendix B: Team Dynamics

We all worked well together. Overall there was a fairly even distribution of work. We learned a lot and we had quite a few laughs together during group meetings. There really isn’t that much to report.